\section*{Introduction}
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For human being to recognize emotions is quite easy. We don't really need to think about it. For an artificial intelligence that is not so simple. Artificial neural networks are widely used in this kind of application : by imitating human mechanism it is more probable to get the same behavior. 
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The goal in this project is to find from a set of figures which one represent which kind of emotion. Only four emotions are represented : mad, sad, happy and mischievous. The differences lay in two points : the eyes and the mouth.
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In this report is first explained what is a neural network, and how it can compute solution. The second part is about the training phase, i.e. how the network learns to differentiate emotions. As images are a bit noisy, they are subject to a preprocessing phase, which is explained in the third part. The forth part deals with adaptation of parameters and show a set of executions. Finally the code architecture is developed.